Researchers in France are working on creating a French network of researchers to organize interaction, communication and training in #computationalneuroscience

If you are a CompNeuro working in France, consider joining, and registering to our mailing list: https://listes.services.cnrs.fr/wws/subscribe/rt_neurocomp

https://bsky.app/profile/lauradugue.bsky.social/post/3lo6rrtvb3k2v
https://www.linkedin.com/posts/laura-dugu%C3%A9-59964756_rtneurocomp-r%C3%A9seau-fran%C3%A7ais-de-neurosciences-activity-7324039702427090944-LKsN

A few weeks ago, I shared a differential equations tutorial for beginners, written from the perspective of a neuroscientist who's had to grapple with the computational part. Following up on that, I've now tackled the first real beast encountered by most computational neuroscience students: the Hodgkin-Huxley model.

While remaining incredibly elegant to this day, this model is also a mathematically dense system of equations that can overwhelm and discourage beginners, especially those with non-mathematical backgrounds. Similar to the first tutorial, I've tried to build intuition step-by-step, starting with a simple RC circuit, layering in Na⁺ and K⁺ channels, and ending with the full spike-generation story.

Feedback is welcome, especially from fellow non-math converts.
https://neurofrontiers.blog/building-a-virtual-neuron-2/

#ComputationalNeuroscience #Python #hodgkinHuxleyModel #math #biophysics

From: @neurofrontiers
https://neuromatch.social/@neurofrontiers/114150087773204813

How do babies and blind people learn to localise sound without labelled data? We propose that innate mechanisms can provide coarse-grained error signals to boostrap learning.

New preprint from @yang_chu.

https://arxiv.org/abs/2001.10605

Thread below

When I transitioned from cognitive to computational neuroscience, I found myself in a bit of a bind. I had learned calculus, but I had progressed little beyond pattern recognition: I knew which rules to apply to find solutions to which equations, but the equations themselves lacked any sort of real meaning for me.

So I struggled with understanding how formulas could be implemented in code and why the code I was reading could be described by those formulas. Resources explaining math “for neuroscientists” were unfortunately quite useless for me, because they usually presented the necessary equations for describing various neural systems, assuming the presence of that basic understanding/intuition I lacked.

Of course, I figured things out eventually (otherwise I wouldn’t be writing about it), but I’m 85% sure I’m not the only one who’s ever struggled with this, and so I wrote the tutorial I wish I could’ve had. If you’re in a similar position, I hope you’ll find it useful. And if not, maybe it helps you get a glimpse into the struggles of the non-math people in your life. Either way, it has cats.

https://neurofrontiers.blog/building-a-virtual-neuron-1/

What's the right way to think about modularity in the brain? This devilish question is a big part of my research now, and it started with this paper with @GabrielBena finally published after the first preprint in 2021!

https://www.nature.com/articles/s41467-024-55188-9

We know the brain is physically structured into distinct areas ("modules"?). We also know that some of these have specialised function. But is there a necessary connection between these two statements? What is the relationship - if any - between 'structural' and 'functional' modularity?

TLDR if you don't want to read the rest: there is no necessary relationship between the two, although when resources are tight, functional modularity is more likely to arise when there's structural modularity. We also found that functional modularity can change over time! Longer version follows.

#religion/ #spiritualism is just very low-res #folkPsychology; folk psychology is low-res #psychology/ #neuroscience; psychology/neuroscience is low-res #computationalNeuroscience, which in turn is low-res #informationPhysics

@NicoleCRust I listened to your Keynote Lecture at the CCN 2024. I loved it. Why do I have to wait till the spring of 2025 for your book to be published?
#neuroscience #cognitivescience #computationalneuroscience #psychiatry #ComplexDynamicalSystems
https://www.youtube.com/watch?app=desktop&v=m47qHAJftR4

We are finally on Mastodon, time for a little #introduction !

Brian is a #FOSS simulator for biological #SpikingNeuralNetworks, for research in #ComputationalNeuroscience and beyond. It makes it easy to go from a high-level model description in Python, based on mathematical equations and physical units, to a simulation running efficiently on the CPU or GPU.

We have a friendly community and extensive documentation, links to everything on our homepage: https://briansimulator.org

This account will mostly announce news (releases, other notable events), but we're also looking forward to discussing with y'all

Jezebel: Sex. Celebrity. Politics. With Teeth: Celebs Inexplicably Let Meta Make AI Bots of Them, Despite SAG’s Explicit Warnings https://jezebel.com/meta-ai-celebrity-chatbots-1850919667 #Jezebel #generativeartificialintelligence #artificialgeneralintelligence #computationalneuroscience #artificialintelligence #entertainmentculture #emergingtechnologies #scarlettjohansson #youtubermrbeast #markzuckerberg #syntheticmedia #justintrudeau #kendalljenner #humaninterest #metaplatforms #deeplearning

Hi #Neuromatchstodon! I joined #mastodon and this server in August of this year after completing for the first time the @neuromatch academy interactive track of #ComputationalNeuroscience. Here is my #introduction:

I am Nanevie, a computational scientist with a passion for #CognitiveScience, #ComputationalNeuroscience, and #EducationalNeuroscience. I am passionate about using computational methods to solve problems in these fields.

I am a recent graduate with a master's degree in Video Games, Digital Interaction, and Big Data from Université Cheikh Anta Diop de Dakar in Senegal. I am currently doing a Research Master's degree in Natural and Artificial Cognition in France at Grenoble INP - Phelma and an MS in Inclusive and Special Education at University of Glasgow.

I have a strong foundation in computer science, but I am also eager to learn more about cognitive science, educational neuroscience, and #MachineLearning. I am confident that I can make a significant contribution to this field. I am currently seeking a research position in the intersection of cognitive science, educational neuroscience, and artificial intelligence.

I am excited to be a part of this community and to learn from all of you. I look forward to collaborating on projects and sharing ideas.

Thanks for having me!

My first post in Mastodon!
I'm Nosrat, I'm doing my PhD in computational neuroscience in university of Geneva.
I’m working on understanding underlying dynamics via direct measurement of neural spiking under the supervision of Timothée Proix.
A repost would be amazing as I’m finding my network here in Mastodon.
#neuroscience #computationalneuroscience

In my commentary on Bowers et al. (BBS, 2022), based on research on human perceptual learning and action-oriented theories of perception, I argue that to develop DNNs that truly model human vision foremost requires a conceptual shift: from treating perception as a largely bottom-up process, to approaching perception as an active, top-down guided process.

My commentary: https://psyarxiv.com/urhq7/
Bowers et al.: https://www.cambridge.org/core/journals/behavioral-and-brain-sciences/article/abs/deep-problems-with-neural-network-models-of-human-vision/ABCE483EE95E80315058BB262DCA26A9

Hey! New to mastodon. Hoping to connect to folks posting about #neuroscience, #academia, #antiracism, #BlackInNeuro, #BlackInSTEM, etc. I did my #phd in #computationalneuroscience and am a #postdoc in an #NIH #IRACDA program at #JHU researching cognitive control and decision making through modeling behavioral and intracranial EEG data. I am teaching at Coppin State University, an #HBCU in #Baltimore. Interested in science and activism.

#introduction

Hi, I am a #datascience researcher based in Germany, currently travelling through Australia (being a tourist in my homeland) for 6 months.

My interests are #machinelearning, #statistics and #computationalneuroscience, particularly applied to medicine, human biology, genetics and health, although my work so far has been mainly in anomaly detection for various other applications.

I am also a bibliophile, pole dancer, fitness freak and occasional gamer.

After finally finding a place that feels more like home on mastodon, here goes the #introduction:
I am a PhD candidate in #computationalneuroscience at the University of Tübingen and Max Planck Institute for Biological Cybernetics, Germany.

I am interested in understanding the relationship between brain computations and dynamics. That's why I study population neural dynamics and their correlation structure underlying different behaviors (e.g., during selective attention tasks).

Looking forward to interactions in this space!

Just moved to neuromatch.social, so here it goes (again), #introduction :

Hi everyone, I'm a last year undergrad in #Neuroscience & #ComputerScience at McGill. I'm doing #ComputationalNeuroscience research in the Baillet Lab at The Neuro (MNI), focusing on whole-brain dynamical models of coupled neural masses calibrated to #MEG #Neuroimaging data (more details @ https://neurolife77.github.io/ if anyone is curious).

I am also the VP of the #MachineLearning committee at PharmaHacks, a hackathon that blends #Biology & #DataScience with a focus on #Pharma.
@neuroscience #neurodon

------------------------ Bonus ------------------------

Since I have the space to put it in the same post now, thanks to the freedom in post length from this new server, here's a bonus:

I regularly share links to preprints that catch my attention and tag them with: #arxivfeed

I started doing this because I thought that the arxiv bots on mastodon were not super efficient, but after doing it for about a month I'd say it's also a good way to keep some form of history of my nightly exploration of the literature in my fields of interest. I usually share stuff about #ComputationalNeuroscience, #Neuroimaging, #DynamicalSystems, #MachineLeaning, #ArtificialIntelligence, etc.

Disclaimer: I usually only read the abstract or skim through them at the time of posting.
Disclaimer 2: I am definitely not consistent.

#introduction:
Research Engineer (#RSE) in #ComputationalNeuroscience, working at the Institut de la Vision in Paris, France. Main developer of the Brian simulator, a simulator for biological SNNs (https://briansimulator.org).
Interested in improving how we do computational science – via my work on software tools, but also by contributing to initiatives that aim to make it more visible, robust, and accessible. Very interested in #visualization, and more efficient science communication.

#introduction

HI! I'm a middle-aged Pilipino #TechGeneralist doing #SoftwareEngineering and #training. I know #java #golang a bit of #devops

I'm a lifelong learner with a lot of interests. I have a degree in #mathematics which I'm now reviewing so I could really delve into #computationalneuroscience

I love music, so I do #voice #piano I'm learning #guitar (acoustic to be more precise). I also love to write #Ghostbusters fanfic. I sometimes do #bookbinding and #leatherwork.